Searching across hundreds of databases
The use of ontologies to control vocabulary and structure annotation has added value to genome-scale data, and contributed to the capture and re-use of knowledge across research domains. Gene Ontology (GO) is widely used to capture detailed expert knowledge in genomic-scale datasets and as a consequence has grown to contain many terms, making it unwieldy for many applications. To increase its ease of manipulation and efficiency of use, subsets called GO slims are often created by collapsing terms upward into more general, high-level terms relevant to a particular context. Creation of a GO slim currently requires manipulation and editing of GO by an expert (or community) familiar with both the ontology and the biological context. Decisions about which terms to include are necessarily subjective, and the creation process itself and subsequent curation are time-consuming and largely manual.
Pubmed ID: 20929524 RIS Download
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.
View all literature mentionsA curated database that provides comprehensive integrated biological information for Saccharomyces cerevisiae along with search and analysis tools to explore these data. SGD allows researchers to discover functional relationships between sequence and gene products in fungi and higher organisms. The SGD also maintains the S. cerevisiae Gene Name Registry, a complete list of all gene names used in S. cerevisiae which includes a set of general guidelines to gene naming. Protein Page provides basic protein information calculated from the predicted sequence and contains links to a variety of secondary structure and tertiary structure resources. Yeast Biochemical Pathways allows users to view and search for biochemical reactions and pathways that occur in S. cerevisiae as well as map expression data onto the biochemical pathways. Literature citations are provided where available.
View all literature mentionsOBO-Edit is an open source, platform-independent application written in Java for viewing and editing any OBO format ontologies. OBO-Edit is a graph-based tool; its emphasis on the overall graph structure of an ontology provides a friendly interface for biologists, and makes OBO-Edit excellent for the rapid generation of large ontologies focusing on relationships between relatively simple classes. The UI components are cleanly separated from the data model and data adapters, so these can be reused in other applications. The oboedit foward-chaining reasoner can also be used independently (for example, for traversing ontology graphs). OBO-Edit uses the OBO format flat file. See the GO wiki, http://wiki.geneontology.org/index.php/OBO-Edit:_Getting_the_Source_Code, for instructions on downloading the source code. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
View all literature mentionsgo-perl is a set of Perl modules for parsing, manipulating and exporting ontologies and annotations. It includes parsers for the OBO and GO gene association file formats. It has a graph-based object model with methods for graph traversal. For more details, see the documentation included with the modules. go-perl comes bundled with XSL (Extensible Stylesheet Language) transforms (which can also be used independently of Perl, provided you have files in OBO-XML format), as well as scripts that can be used as standalone tools. Installation should be simple, provided you have some experience with Perl and CPAN; see the INSTALL file for details. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
View all literature mentionsA collaboration involving developers of science-based ontologies who are establishing a set of principles for ontology development with the goal of creating a suite of orthogonal interoperable reference ontologies in the biomedical domain. In addition to a listing of OBO ontologies, this site provides a statement of the OBO Foundry principles, discussion fora, technical infrastructure, and other services to facilitate ontology development. Feedback is welcome and participation encouraged.
View all literature mentionsIntegrated public bioinformatics resource to support genomic, proteomic and systems biology research and scientific studies. Provides databases and protein sequence analysis tools to scientific community, including Protein Sequence Database which grew out from the Atlas of Protein Sequence and Structure. Conducts research in biomedical text mining and ontology, computational systems biology, and bioinformatics cyberinfrastructure. In 2002 PIR, along with its international partners, EBI (European Bioinformatics Institute) and SIB (Swiss Institute of Bioinformatics), were awarded a grant from NIH to create UniProt, a single worldwide database of protein sequence and function, by unifying the PIR-PSD, Swiss-Prot, and TrEMBL databases. Currently, PIR major activities include: i) UniProt (Universal Protein Resource) development, ii) iProClass protein data integration and ID mapping, iii) PRO protein ontology, and iv) iProLINK protein literature mining and ontology development. The FTP site provides free download for iProClass, PIRSF, and PRO.
View all literature mentionsService providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
scicrunch.org
